完备的 AI 学习路线 https://mp.weixin.qq.com/s/fUNDdCzJrWBoKYh1tT4gSw
CS229 课程讲义中文翻译: https://kivy-cn.github.io/Stanford-CS-229-CN/#/?id=%e8%b4%a1%e7%8c%ae%e6%8c%87%e5%8d%97
JerryLead 斯坦福笔记: https://www.cnblogs.com/jerrylead/default.html?page=3
西瓜书公式推导: https://datawhalechina.github.io/pumpkin-book/#/chapter4/chapter4
神经网络与深度学习: https://nndl.github.io/
深度机器学习数学知识: https://blog.csdn.net/xbinworld?t=1
线性代数笔记: https://blog.csdn.net/github_40153370?t=1
机器学习中SVD总结: https://mp.weixin.qq.com/s/Dv51K8JETakIKe5dPBAPVg
PCA的数学原理: http://blog.codinglabs.org/articles/pca-tutorial.html
主成分分析PCA原理详解: https://blog.csdn.net/program_developer/article/details/80632779
Machine Learning 汇总: https://www.cnblogs.com/jerrylead/tag/Machine%20Learning/
EM算法: https://www.cnblogs.com/jerrylead/archive/2011/04/06/2006936.html
EM算法-数学原理及其证明: https://blog.csdn.net/yzheately/article/details/51164441
隐马尔可夫模型(HMM): https://www.cnblogs.com/jacklu/p/7753471.html
AI算法工程师手册: http://www.huaxiaozhuan.com/
Python 机器学习在线指南: https://redstonewill.com/2338/
GBDT思想: https://www.cnblogs.com/Sugar-Chl/p/10158672.html
L0、L1与L2范数 https://www.cnblogs.com/zongfa/p/9310668.html
机器学习公开课: http://52opencourse.com/
朴素贝叶斯算法的理解与实现: https://www.cnblogs.com/lliuye/p/9178090.html
阵的迹以及迹对矩阵求导: https://blog.csdn.net/u012421852/article/details/79594933
矩阵求导术: https://zhuanlan.zhihu.com/p/24709748
CS 229-监督学习备忘单: https://stanford.edu/~shervine/teaching/cs-229/cheatsheet-supervised-learning
原文地址:https://www.cnblogs.com/kaobeixingfu/p/11678306.html